CNN-based methods able to perform localization and classification without region proposals have also been proposed for the instance segmentation task. One of the problems they face is that CNNs use pooling operations to enable shift invariance, but that leads to a loss of positional information, especially near the head of network. This is particularly troublesome when it comes to instance segmentation, because positional information is critical for accurate instance segmentation. Networks such as Deep Contour Awareness Networks (DCAN) [1]} make positional awareness explicit at the output of the CNN.
